The overall objective of this study is to characterize fully the dose nd volume response of GI and GU morbidity from conformal therapy of cancer of the prostate. The database in the Department of Radiation Oncology at Fox Chase Cancer Center contains extensive data on more than 1200 patients with cancer of the prostate. Using these data and generating dose-volume histograms of the rectal and bladder walls for each patient seen since the installation of the department's CT simulator, we will be able to establish the dose-volume response and the important of co- morbidities for acute grade 2 and late grade 2 and 3 GI and GI complications of cancer and the prostate. Specifically, 1. Using logistic regression, we will determine the factors that are significantly related to the incidence of acute grade 2 GI and GI morbidity. Analyzing GI and GI morbidity separately, we will use logistic regression to assess the relationship of tumor factors, co- morbidities, treatment factors, and factors in the medical history to these morbidities. 2. Using the proportional hazards model, we will determine the factors that are significantly related to the incidence of late grade 2 and grade 3 GI and GI morbidity. Time at risk and time to onset of symptoms are variable. Therefore, the proportional hazards model, accounting for censoring, will be used to determine the significance of factors putatively related to these late effects. GI and GI morbidities and grades 2 and 3 morbidities will be analyzed separately. 3. Using a maximum likelihood method, we will fit a dose response model to the incidence of late grade 2 and grade 3 GO and GU morbidity, accounting for the relative risk of factors determined by the proportional hazards analysis. The above proportional hazards modeling can determine whether dose is significantly related to complications, but it will not produce a dose-response function. The dose-volume response function will be obtained by using maximum likelihood estimation to fit various dose-volume response models to our data. The relative risk for factors determined to be important from Specific Aim 3 will be accounted for in these models. 4. We will determine whether these data suggest if any of the various treatment techniques used in conformal radiation treatment of the prostate cam be shown to be significantly superior. The results of dose- volume response modeling will be used to predict the incidence of complications for these various techniques to determine if any technique is superior. 5. The model(s) of dose-volume response obtained in aims 2 and 3 will be validated. The database will be "frozen" at the initiation of this project, and these data will be used in the analysis described thus far. Patients treated during the first 3 years of this project will be analyzed separately during the last year using the models obtained up to that time. This form of data splitting will be used to determine if the model(s) fit the new data, thereby validating the initial results.